Exploring resilience and competitiveness of wine estates in Languedoc-Roussillon in the recent past: a multi-level perspective

Grapevines interact with the climate (aboveground) and the soil (belowground), affecting the characteristics of winegrapes produced. These interactions are impacted by climate change, the erosion of biodiversity, and losses of soil organic matter (SOM).

Grape typicity valorization can significantly enhance viticultural sector competitiveness to the extent that contributes to the development of a wine so distinctive and unique. This work leads to the characterization of the grapes through indicators expressing environmental effects.

The main innovation in the VINIoT service is the joint use of two technologies that are currently used separately: vineyard monitoring using multispectral imaging and deployed terrain sensors. One part of the system is based on the development of artificial intelligence algorithms that are feed on the images of the multispectral camera and IoT sensors, high-level information on water stress, grape ripening status and the presence of diseases. In order to obtain algorithms to determine the state of ripening of the grapes and avoid losing information due to the diversity of the grape berries, it was decided to work along the first year 2020 at berry scale in the laboratory, during the second year at the cluster scale and on the last year at plot scale. Different varieties of white and red grapes were used; in the case of Galicia we worked with the white grape variety Treixadura and the red variety Mencía. During the 2020 and 2021 campaigns, multispectral images were taken in the visible and infrared range of: 1) sets of 100 grapes classifying them by means of densimetric baths, 2) individual bunches. The images taken with the laboratory analysis of the ripening stage were correlated. Technological maturity, pH, probable degree, malic acid content, tartaric acid content and parameters for assessing phenolic maturity, IPT, anthocyanin content were determined. It has been calculated for each single image the mean value of each spectral band (only taking into account the pixels of interest) and a correlation study of these values with laboratory data has been carried out. These studies are still provisional and it will be necessary to continue with them, jointly with the training of the machine learning algorithms. Processed data will allow to determine the sensitivity of the multispectral images and select bands of interest in maturation.

The wine sector is being directly affected by climate change. Temperatures above 30ºC can cause a lag between the ripening of the berry pulp (a rapid increase in sugar content) and the skin

The objective of the present work was to study the influence of the foliar application of seaweed (Laminaria japonica), on the bunch and on the must in the ‘Cabernet Sauvignon’ grape. The experiment was carried out in the years 2021/2022, in a 21-year-old commercial vineyard, in the municipality of “Dom Pedrito” – “Rio Grande do Sul” (RS). A completely randomized experimental design was used, with 4 treatments and 4 replications (7 plants per replication). The treatments were: T1- control treatment; T2- Exal Powder 5 g L-1; T3- Hidro Exal 15 ml L-1; T4- Exal Powder 5 g L-1+ Hidro Exal 15 ml L-1.